code: def spline_bin_size_constraint(x, lo=-1, hi=1, dtype=tf.float32):
      """Maps innermost axis of `x` to positive values."""
      nbins = tf.cast(tf.shape(x)[-1], dtype)
      min_width = 1e-2
      scale = hi - lo - nbins * min_width
      return tf.math.softmax(tf.cast(x, dtype)) * scale + min_width
  
imports: import collections
  import inspect
  from absl import logging
  import hypothesis.strategies
  import tensorflow.compat.v2
  from tensorflow_probability.python import bijectors
  from tensorflow_probability.python.distributions import lkj
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import hypothesis_testlib
  from tensorflow_probability.python.internal import tensorshape_util
label_desc: Use image node_id 8 for calling a global function with example usage: spline_bin_size_constraint(x, lo, hi, dtype) and returns: unknown